APSCE Webinar #19: From Learning Object to Learning Cell, A Resource Organization Model for Ubiquitous Learning

APSCE Webinar #19: From Learning Object to Learning Cell, A Resource Organization Model for Ubiquitous Learning

02 Nov 2021 Published Public 10:00:00 Asia/Taipei (UTC+08:00) Online

Speakers: Prof. Shengquan YU (Beijing Normal University, China)

Moderator: Dr. Jon MASON (Charles Darwin University, Australia)

Curated by APSCE Advanced Learning Technologies, Learning Analytics, Platforms & Infrastructure SIG

Date: 2 November 2021 (Tuesday)
Time: 10:00-11:00 (GMT+8)

FREE Registration (due 30 October): https://apsce.net/webinar

With the development of pervasive computing and sensor networks, digital space is increasingly merged with physical space, forming a ubiquitous information space encompassing both the real world and virtual worlds. Ubiquitous learning, a context-aware, social, informal and adaptive type of learning, is therefore becoming increasingly realizable. The key to implementing ubiquitous learning is the construction and organization of learning resources. While current research on ubiquitous learning has primarily focused on conceptual models, empirical research that explores ways to organize easily accessible and on-demand learning resources is also crucial. This research presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a semantic gene (knowledge ontology) into the model, Learning Cell can flexibly describe the internal structure and external relations of learning resources, allowing the evolution of learning resources to occur in an orderly way. Furthermore, by employing a computational model of a social cognition network, Learning Cell enables not only materialized resource sharing but also the sharing of social cognition networks. Finally, by separately deploying resource structures and resource content in the cloud storage model, Learning Cell achieves context awareness of u-Learning resources. Learning Cell represents a resource aggregation model that is different from the learning object model. It makes up for the defects of existing learning technologies in the following areas: the sharing of process information and social cognition networks, the intelligence of resources, and the evolution of content. Learning Cell provides a theoretical framework of u-Learning resource organization.

  • Start Time
    02 Nov 2021 10:00:00 Asia/Taipei (UTC+08:00)
  • Finish Time
    02 Nov 2021 11:00:00 Asia/Taipei (UTC+08:00)
  • Location
Shengquan YU
Beijing Normal University
Jon Mason
Charles Darwin University